# Copyright 2020 - 2022 MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#     http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import torch
from torch.nn.functional import normalize
import numpy as np


class Loss(torch.nn.Module):
    def __init__(self, args):
        super().__init__()
        self.recon_loss = torch.nn.MSELoss().cuda()

    def __call__(self, output_recons, target_recons):
        recon_loss = self.recon_loss(output_recons, target_recons)
        return recon_loss


if __name__ == '__main__':
    pass